Margin of Error
How to find the margin of error from the sample proportion: definition, formula, 1 example, and its solution.
Sample Proportion
Definition
In reality,
we don't know the p (proportion)
of the whole data (population).
So, to find the p,
we pick a sample
and find the proportion of the sample:
p^.
p^ is read as [p hat].
Formula
Formula
But p^ and p cannot be always the same.
The sample cannot always represent
the whole population.
Then people found out that,
under a certain confidence level,
p is in this interval.
p^ - Z√[p^⋅q^]/n ≤ p ≤ p^ + Z√[p^⋅q^]/n
Shortly, p is in
p^ ± Z√[p^⋅q^]/n.
This Z√[p^⋅q^]/n
is the margin of error.
Z: Z-score (related to the confidence level)
p^: Probability (proportion) of the wanted event
q^ = 1 - p^
n: Number of the values of the sample
As you can see,
if n (sample number) increases,
the margin of error decreases.
So we can determine p (population proportion)
more precisely.
But if n increases,
you need more resources (time, money)
to find p.
So it's good to find the right n.
Example
Example
Solution
It says
in a random sample,
64% of the people favored the candidate A.
So the sample proportion is
p^ = 0.64.
p^ = 0.64
Then q^ = 1 - 0.64.
This q^ means
the sample proportion of the people
not favored the candidate A.
Probability: Not A
1 - 0.64 = 0.36.
The sample number is 256.
So n = 256.
p^ = 0.64
q^ = 0.36
n = 256
Then [p^⋅q^]/n = [0.64⋅0.36]/256.
Multiply 1002
to both of the numerator and the denominator.
Then [64⋅36]/[256⋅1002].
64 = 26
36 = 22⋅32
256 = 28
Prime Factorization
Cancel 26⋅22 in the numerator
and cancel the denominator 28.
32/1002 = [3/100]2
Power of a Quotient
3/100 = 0.03
Find the z-score.
It says
P(0 ≤ Z ≤ 1.96) = 0.4750.
Recall that
for the normal distribution curve,
the left side and the right side
are the same.
So P(-1.96 ≤ Z ≤ 1.96) = 0.4750⋅2 = 0.95.
P(-1.96 ≤ Z ≤ 1.96) = 0.95 means
the z-score for 95% is Z = 1.96.
So Z = 1.96.
Then the margin of error, ME,
is equal to,
the z-score, 1.96
times
square root, [p^⋅q^]/n, 0.032.
So the margin of error is
(ME) = 1.96⋅√0.032.
√0.032 = 0.03
Square Root
1.96⋅0.03 = 0.0588
0.0588 = 5.88%
So the margin of error is 5.88%.
This means
for 95% probability,
the candidate A's favorability rating is
64% ± 5.88%:
58.12% ~ 69.88%.